opencv3学习笔记-FLANN匹配

#include<opencv2\opencv.hpp>
#include<opencv2\xfeatures2d\nonfree.hpp>
#include<iostream>

using namespace cv;
using namespace std;
using namespace xfeatures2d;
//全局变量声明
/*Mat srcimage1, srcimage2, midimage1,midimage2, dstimage;
char label[20], label2[20];
//主函数
int main()
{
	srcimage1 = imread("left.png");
	srcimage2 = imread("right.png");
	cvtColor(srcimage1, midimage1, COLOR_BGR2GRAY);
	cvtColor(srcimage2, midimage2, COLOR_BGR2GRAY);
	GaussianBlur(midimage1, midimage1, Size(7, 7), 2, 2);
	GaussianBlur(midimage2, midimage2, Size(3, 3), 2, 2);
	vector<Vec3f> circles1, circles2;
	HoughCircles(midimage1, circles1, HOUGH_GRADIENT, 1, 300, 110, 55, 100, 0);
	HoughCircles(midimage2, circles2, HOUGH_GRADIENT, 1.5, 10, 200, 100, 100, 0);

	for (size_t i = 0; i < circles1.size(); i++)
	{
		Point2f center1(circles1[i][0], circles1[i][1]);
		float radius1 = circles1[i][2];
		circle(srcimage1, center1, 1, Scalar(0, 255, 0), -1, 8, 0);
		circle(srcimage1, center1, radius1, Scalar(155, 50, 255), 2, 8, 0);
		sprintf(label, "(%.3f,%.3f)", center1.x, center1.y);
		putText(srcimage1, label, center1, FONT_HERSHEY_PLAIN, 1, Scalar(0, 150, 255), 1, 8, 0);
	}
	for (size_t j = 0; j < circles2.size(); j++)
	{
		Point2f center2(circles2[j][0], circles2[j][1]);
		float radius2 = circles2[j][2];
		circle(srcimage2, center2, 1, Scalar(0, 255, 0), -1, 8, 0);
		circle(srcimage2, center2, radius2, Scalar(155, 50, 255), 2, 8, 0);
		sprintf(label2, "(%.3f,%.3f)", center2.x, center2.y);
		putText(srcimage2, label2, center2, FONT_HERSHEY_PLAIN, 1, Scalar(0, 150, 255), 1, 8, 0);
	}
	imshow("识别左图", srcimage1);
	imshow("识别右图", srcimage2);
	waitKey(0);

	return 0;
}*/

int main()
{
	Mat srcimage1 = imread("left.png");
	Mat srcimage2 = imread("right.png");

	int minhessian=300;
	Ptr<SurfFeatureDetector>detector = SurfFeatureDetector::create(minhessian);
	vector<KeyPoint>keypoints_1, keypoints_2;
	detector->detect(srcimage1, keypoints_1);
	detector->detect(srcimage2, keypoints_2);

	Ptr<SurfDescriptorExtractor>extractor = SurfDescriptorExtractor::create();
	Mat descriptors_1, descriptors_2;
	extractor->compute(srcimage1, keypoints_1, descriptors_1);
	extractor->compute(srcimage2, keypoints_2, descriptors_2);

	FlannBasedMatcher matcher;
	vector<DMatch>matches;
	matcher.match(descriptors_1, descriptors_2, matches);

	double max_dist = 0; double min_dist = 100;
	for (int i = 0; i < descriptors_1.rows; i++)
	{
		double dist = matches[i].distance;
		if (dist < min_dist)
			min_dist = dist;
		if (dist > max_dist)
			max_dist = dist;
	}
	printf(">最大距离:%f\n", max_dist);
	printf(">最小距离:%f\n", min_dist);

	vector<DMatch>goodmatches;
	for (int i = 0; i < descriptors_1.rows; i++)
	{
		if (matches[i].distance <1.3* min_dist)
		{
			goodmatches.push_back(matches[i]);
		}
	}


	Mat img_matches;
	drawMatches(srcimage1, keypoints_1, srcimage2, keypoints_2, goodmatches, img_matches, Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);

	for (int i = 0; i < goodmatches.size(); i++)
	{
		printf(">符合条件的匹配点【%d】特征点1：%d--特征点2：%d\n", i, goodmatches[i].queryIdx, goodmatches[i].trainIdx);

	}

	imshow("匹配效果图", img_matches);

	waitKey(0);
	return 0;

}